Prepare TFMA for 0.14.0 release

PiperOrigin-RevId: 262029761

Author: mdreves

README.md

@@ -62,7 +62,8 @@ combinations may also work.
 
 |tensorflow-model-analysis                                                           |tensorflow    |apache-beam[gcp]|
 |------------------------------------------------------------------------------------|--------------|----------------|
-|[GitHub master](https://github.com/tensorflow/model-analysis/blob/master/RELEASE.md)|nightly (1.x) |2.11.0          |
+|[GitHub master](https://github.com/tensorflow/model-analysis/blob/master/RELEASE.md)|nightly (1.x) |2.14.0          |
+|[0.14.0](https://github.com/tensorflow/model-analysis/blob/v0.14.0/RELEASE.md)      |1.14          |2.14.0          |
 |[0.13.1](https://github.com/tensorflow/model-analysis/blob/v0.13.1/RELEASE.md)      |1.13          |2.11.0          |
 |[0.13.0](https://github.com/tensorflow/model-analysis/blob/v0.13.0/RELEASE.md)      |1.13          |2.11.0          |
 |[0.12.1](https://github.com/tensorflow/model-analysis/blob/v0.12.1/RELEASE.md)      |1.12          |2.10.0          |

RELEASE.md

@@ -1,4 +1,4 @@
-# Current version (not yet released; still in development)
+# Current version 0.14.0
 
 ## Major Features and Improvements
 
@@ -29,7 +29,6 @@
 *   Make metrics-related operations thread-safe by wrapping them with locks.
     This eliminates race conditions that were previously possible in
     multi-threaded runners which could result in incorrect metric values.
-*   Depends on `apache-beam[gcp]>=2.12,<3`.
 *   More flexible `FanoutSlices`.
 *   Limit the number of sampling buckets to 20.
 *   Improved performance in Confidence Interval computation.
@@ -39,12 +38,17 @@
 *   Added support for example weight keys for multi-output models.
 *   Added option to set the desired batch size when calling run_model_analysis.
 *   Changed TFRecord compression type from UNCOMPRESSED to AUTO.
+*   Depends on `apache-beam[gcp]>=2.14,<3`.
+*   Depends on `numpy>=1.16,<2`.
+*   Depends on `protobuf>=3.7,<4`.
+*   Depends on `scipy==1.1.0`.
 
 ## Breaking changes
 
 *   Removed uses of deprecated tf.contrib packages (where possible).
 *   `tfma.default_writers` now requires the `eval_saved_model` to be passed as
     an argument.
+*   Requires pre-installed TensorFlow >=1.14,<2.
 
 ## Deprecations
 

g3doc/install.md

@@ -58,7 +58,9 @@ combinations may also work.
 
 |tensorflow-model-analysis                                                           |tensorflow    |apache-beam[gcp]|
 |------------------------------------------------------------------------------------|--------------|----------------|
-|[GitHub master](https://github.com/tensorflow/model-analysis/blob/master/RELEASE.md)|nightly (1.x) |2.11.0          |
+|[GitHub master](https://github.com/tensorflow/model-analysis/blob/master/RELEASE.md)|nightly (1.x) |2.14.0          |
+|[0.14.0](https://github.com/tensorflow/model-analysis/blob/v0.14.0/RELEASE.md)      |1.14          |2.14.0          |
+|[0.13.1](https://github.com/tensorflow/model-analysis/blob/v0.13.1/RELEASE.md)      |1.13          |2.11.0          |
 |[0.13.0](https://github.com/tensorflow/model-analysis/blob/v0.13.0/RELEASE.md)      |1.13          |2.11.0          |
 |0.12.1                                                                              |1.12          |2.10.0          |
 |0.12.0                                                                              |1.12          |2.10.0          |

setup.py

@@ -254,24 +254,24 @@ def run(self):
     # protobuf) with TF.
     'install_requires': [
         # Sort alphabetically
-        'apache-beam[gcp]>=2.12,<3',
+        'apache-beam[gcp]>=2.14,<3',
         'ipywidgets>=7,<8',
         'jupyter>=1,<2',
-        'numpy>=1.14.5,<2',
+        'numpy>=1.16,<2',
         'protobuf>=3.7,<4',
         # TODO(b/126957988): Stop pinning scipy when possible.
         'scipy==1.1.0',
         # For apitools.
         # Note: try version 1.10 if error "metaclass conflict: the
         # metaclass of a derived class must be a (non-strict) subclass of the
         # metaclasses of all its bases" occurred in future.
-        'six>=1.9,<2',
+        'six>=1.10,<2',
         # TODO(xinzha): Uncomment this once TF can automatically select between
         # CPU and GPU installation.
-        # 'tensorflow>=1.13,<2',
+        # 'tensorflow>=1.14,<2',
         # TODO(b/68765743): replace it with tfx-base after it's available
         # (b/72384547)
-        'tensorflow-transform>=0.13,<1',
+        'tensorflow-transform>=0.14,<1',
     ],
     'python_requires': '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,<4',
     'packages': find_packages(),
@@ -297,10 +297,8 @@ def run(self):
         'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.5',
-        # TODO(b/125613675): Once Beam supports Python 3.6 and 3.7, uncomment
-        # these lines.
-        # 'Programming Language :: Python :: 3.6',
-        # 'Programming Language :: Python :: 3.7',
+        'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
         'Topic :: Scientific/Engineering',
         'Topic :: Scientific/Engineering :: Mathematics',
         'Topic :: Scientific/Engineering :: Artificial Intelligence',

tensorflow_model_analysis/api/model_eval_lib.py

@@ -61,9 +61,9 @@ def _assert_tensorflow_version():
   """Check that we're using a compatible TF version."""
   # Fail with a clear error in case we are not using a compatible TF version.
   major, minor, _ = tf.version.VERSION.split('.')
-  if int(major) != 1 or int(minor) < 13:
+  if int(major) != 1 or int(minor) < 14:
     raise RuntimeError(
-        'Tensorflow version >= 1.13, < 2 is required. Found (%s). Please '
+        'Tensorflow version >= 1.14, < 2 is required. Found (%s). Please '
         'install the latest 1.x version from '
         'https://github.com/tensorflow/tensorflow. ' % tf.version.VERSION)
 

tensorflow_model_analysis/version.py

@@ -15,4 +15,4 @@
 
 # Version string for this release of TFMA.
 # Note that setup.py reads and uses this version.
-VERSION_STRING = '0.14.0dev'
+VERSION_STRING = '0.14.0'